A Road Map for Translational Research on Artificial Intelligence in Medical Imaging: From the 2018 National Institutes of Health/RSNA/ACR/The Academy Workshop

Developing an Artificial Intelligence–Enabled Health Care Practice: Rewiring Health Care Professions for Better Care

“…Artificial intelligence (AI) in health care has grown enormously over the last decade, and it has the potential to transform the delivery of care. The number of studies and research initiatives in health care continues to grow, and yet there remains a fundamental lack of understanding of how AI can and should be used in many health care fields [1] and how the health professions must evolve. AI is the branch of computer science that is designed to artificially create and simulate human-like intelligent behavior in complex machines [2].…”

“…AI recognizes patterns [2] that inform many aspects of care, including preventative and public health care, diagnosis, treatment, prognosis, and predictive health services. Although AI is still in its early development with respect to clinical readiness [1,2], its applications have resulted in major practical and theoretical advancements in several health care domains and related fields [2].…”

“…Allen et al have made strong recommendations for health care professional involved in the field of imaging. These recommendations include (1) implementing data standards and following them in practice, (2) prioritizing use cases for AI, (3) determining the clinical impact of potential algorithms, (4) describing and articulating the needs of the profession for data scientists and researchers, and (5) participating in the translation of practice needs from human to machine language [1]. These recommendations have been generated from a particular professional perspective, but, in fact, they may have wide applicability for many individual professions and the structure of the organization.…”

Artificial Intelligence in Radiology: Summary of the AUR Academic Radiology and Industry Leaders Roundtable

“…It was noted that the postmarketing stage sometimes is minimized or curtailed during introduction of new healthcare technologies. Although not part of the discussion of this Roundtable, we note the subsequent publication of the Research Roadmap on Medical Imaging Artificial Imaging that followed an August 2018 workshop convened by the National Institute of Biomedical Imaging and Bioengineering at the National Institutes of Health , with participation by other radiology societies, including the American College of Radiology , the Radiological Society of North America , and the Academy for Radiology and Biomedical Research (the Academy) (16).…”

Promises of artificial intelligence in neuroradiology: a systematic technographic review

“…However, other major categories of disease for which neurologists and other specialists request imaging are missing, for example radiculopathy and epilepsy. In defining clinical challenges such as these, radiologists can contribute to translational research in artificial intelligence [28].…”